Officer ‘Ben’ a two-year-old yellow lab, and Officer Jose? Solis make up UND police’s first K-9 unit
Bibliographic record
Abstract
Officer ‘Ben’ a two-year-old yellow lab, and Officer Jose? Solis make up UND police’s first K-9 unit University of North Dakota Police Department (UPD) has sniffed out a new ally, which happens to walk on four legs, is covered in fur and loves tennis balls. This new addition to the UPD goes by the name of "Ben," a two-year-old yellow Labrador retriever, trained to sense narcotics and track people. Officer Ben as he's known– yes, he even gets a rank -- and his handler, Officer Jose? Solis, make up the UPD's first K9 unit. "(Having the K9 Unit) pushes us to the next point of providing greater services to the campus community," said Sgt. Danny Weigel, sergeant of investigations and K9 Unit coordinator. "It offers services that a human physically can't do." With narcotic searches, Ben and Solis will be able to help the UPD locate marijuana, cocaine, methamphetamine and heroin. They will be available to perform narcotics searches in parking lots, residence halls and traffic stops, to name just a few places. The K9 unit will be involved in the tracking of criminals as well as in reuniting missing individuals with friends and loved ones. With his keen nose, Ben is able to track people. For example, if a child wanders away from home Ben, with his keen nose, and Solis would be able to track down the child and keep him or her from harm. Ben will be cared for by Solis, who applied for the position and was chosen through a selection and interview process. "I like to educate our community on narcotics and their effects" said Solis. "And what better way to do that then to get a K9 and work as a handler?" Prior to working as a handler, Solis was assigned to the night shift as well as daytime patrols. He has been with the UPD for three years and is originally from Kerkhoven, Minn. Solis had to go through two weeks of training, of 8-10 hour days, in order to be qualified as Ben's handler. In addition, both Ben and Solis are required to train eight hours each month, but they hope to double that. They will be receiving their national certification from United States Police Canine Association (USPCA) as well. The UND Association of Residence Halls (ARH) provided the initial funding to kick-start the K9 Unit and will be holding a naming contest for the students to select Ben's nickname. With the aid of the K9 Unit, UPD hopes it can continue its success in making the UND campus community a safe place to live, learn and work. "Overall, it's a great program and we're very excited to continue to build relationships with our campus and community," said Weigel. Amy Halvorson University & Public Affairs student writer
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.366 | 0.135 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".